Results 121 to 130 of about 25,829 (292)

Improving model adversarial robustness in Extractive Question Answering via Wasserstein-Guided feature Representations

Alexandria Engineering Journal
Extractive Question Answering (EQA) models aim to locate accurate answers from passages given a question but are highly susceptible to adversarial attacks.
Gang Huang, Lu Zhang, Hailun Wang
doaj   +1 more source

Hardware‐Attentive Programmable Fourier Ptychography Enables Task‐Adaptive Label‐Free Virtual Staining

Advanced Science, EarlyView.
Task‐adaptive programmable optics enables label‐free virtual staining through optical‐attention‐guided acquisition and reconstruction. By optimizing wavelength, illumination angle, exposure time, and imaging depth, the framework learns task‐relevant optical measurements, generating clinically interpretable virtual stains with improved fidelity, non ...
Tianyue He, Wenyi Jing, Le Zhang, Qican Zhang, Tingdong Kou, Xin He, Yan Qiu, Yang Lu, Jian Cui, Yongfu Wen, Zhenrong Zheng, Hongying Zhang, Dayong Jin, Junfei Shen   +13 more
wiley   +1 more source

Robustness Tokens: Towards Adversarial Robustness of Transformers

Recently, large pre-trained foundation models have become widely adopted by machine learning practitioners for a multitude of tasks. Given that such models are publicly available, relying on their use as backbone models for downstream tasks might result in high vulnerability to adversarial attacks crafted with the same public model.
Brian Pulfer, Yury Belousov 0001, Slava Voloshynovskiy   +2 more
openaire   +2 more sources

ORBIT‐AMD: Ordinal Risk, Bilateral Imaging, and Trajectory Learning for Age‐Related Macular Degeneration in Multi‐Cohorts

Advanced Science, EarlyView.
Eligibility flow and real‐world AMD burden in the UKB retinal imaging cohort and TMUEH external‐validation cohort. Overview of the ORBIT‐AMD architecture, integrating retinal representation pretraining, bilateral eye‐graph modeling and concept bottleneck learning to support ordered risk, bilateral context, interpretable lesion concepts, longitudinal ...
Xuehao Cui, Dejia Wen, Patrick Yu‐Wai‐Man, Xiaorong Li   +3 more
wiley   +1 more source

Leveraging Attack Non-Transferability to Boost Adversarial Robustness for Foundation Models

Applied Sciences
This paper presents a novel adversarial defense framework that strategically exploits the non-transferability of adversarial attacks across multi-modal foundation models.
Koshiro Toishi, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama   +4 more
doaj   +1 more source

Holistic Adversarially Robust Pruning

CoRR
Accepted by ICLR ...
Zhao, Qi, Wressnegger, Christian
openaire   +3 more sources

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Adversarially Robust Neural Architectures

IEEE Transactions on Pattern Analysis and Machine Intelligence
13 pages, 5 figures, 8 ...
Minjing Dong, Yanxi Li 0001, Yunhe Wang 0001, Chang Xu 0002   +3 more
openaire   +3 more sources

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Improve Adversarial Robustness of AI Models in Remote Sensing via Data-Augmentation and Explainable-AI Methods

Remote Sensing
Artificial intelligence (AI) has made remarkable progress in recent years in remote sensing applications, including environmental monitoring, crisis management, city planning, and agriculture.
Sumaiya Tasneem, Kazi Aminul Islam
doaj   +1 more source